Quantum-Accelerated Evolutionary Algorithms for Complex Design Space

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

Quantum-accelerated evolutionary algorithms offer a novel approach to complex design space exploration, particularly within fields like materials science and robotics. This paper investigates the potential of quantum annealing and related algorithms to enhance the efficiency of evolutionary optimization processes, leading to the discovery of novel designs with enhanced performance characteristics. The core claim is that quantum-enhanced evolutionary algorithms can drastically reduce the time required to find optimal designs compared to classical methods, opening new possibilities for complex system design. We explore the theoretical foundations, algorithmic implementation, and potential applications of this approach, emphasizing its ability to tackle the inherent complexities of evolving designs.

DOI: 10.5281/zenodo.22219055

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